{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T20:14:41Z","timestamp":1771704881365,"version":"3.50.1"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1109\/icra57147.2024.10610696","type":"proceedings-article","created":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T17:51:05Z","timestamp":1723139465000},"page":"12865-12872","source":"Crossref","is-referenced-by-count":2,"title":["Unsupervised Learning of Neuro-symbolic Rules for Generalizable Context-aware Planning in Object Arrangement Tasks"],"prefix":"10.1109","author":[{"given":"Siddhant","family":"Sharma","sequence":"first","affiliation":[{"name":"IIT Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shreshth","family":"Tuli","sequence":"additional","affiliation":[{"name":"IIT Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rohan","family":"Paul","sequence":"additional","affiliation":[{"name":"IIT Delhi,Computer Science and Engg. (CSE) and Yardi School of AI (ScAI)"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"25 673","article-title":"Neural production systems","volume":"34","author":"Goyal","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref2","first-page":"1861","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","volume-title":"Proceedings of the 35th International Conference on Machine Learning","volume":"80","author":"Haarnoja"},{"key":"ref3","first-page":"113","article-title":"Truly proximal policy optimization","volume-title":"Proceedings of The 35th Uncertainty in Artificial Intelligence Conference","volume":"115","author":"Wang"},{"key":"ref4","article-title":"Nltopddl: One-shot learning of pddl models from natural language process manuals","volume-title":"Proc. of the ICAPS Workshop on Knowledge Engineering for Planning and Scheduling (KEPS). ICAPS","author":"Miglani"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i06.6542"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1129"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-23807-0_20"},{"key":"ref8","first-page":"99","article-title":"Ppddl1. 0: An extension to pddl for expressing planning domains with probabilistic effects","volume":"2","author":"Younes","year":"2004","journal-title":"Techn. Rep. CMU-CS-04-162"},{"key":"ref9","article-title":"Survey: Robot programming by demonstration","author":"Billard","year":"2008","journal-title":"Springrer, Tech. Rep."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1561\/2300000021"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913495721"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3287362"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3171"},{"key":"ref14","article-title":"Learning and using abstractions for robot planning","author":"Shah","year":"2020"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.12"},{"issue":"1","key":"ref16","first-page":"1395","article-title":"A review of robot learning for manipulation: Challenges, representations, and algorithms","volume":"22","author":"Kroemer","year":"2021","journal-title":"The Journal of Machine Learning Research"},{"key":"ref17","first-page":"895","article-title":"Building portable options: Skill transfer in reinforcement learning","volume":"7","author":"Konidaris","year":"2007","journal-title":"Ijcai"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989109"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3187833"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1613\/jair.5575"},{"key":"ref21","article-title":"Learning sparse relational transition models","author":"Xia","year":"2018"},{"key":"ref22","first-page":"30 003","article-title":"Learning-based motion planning in dynamic environments using gnns and temporal encoding","volume":"35","author":"Zhang","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref24","first-page":"11 525","article-title":"Object-centric learning with slot attention","volume":"33","author":"Locatello","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref25","article-title":"Categorical reparameterization with gumbel-softmax","author":"Jang","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2012.2186810"},{"issue":"Nov","key":"ref29","first-page":"397","article-title":"Using confidence bounds for exploitationexploration trade-offs","volume":"3","author":"Auer","year":"2002","journal-title":"Journal of Machine Learning Research"},{"key":"ref30","first-page":"2016","volume-title":"Pybullet, a python module for physics simulation for games, robotics and machine learning","author":"Coumans"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"}],"event":{"name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","location":"Yokohama, Japan","start":{"date-parts":[[2024,5,13]]},"end":{"date-parts":[[2024,5,17]]}},"container-title":["2024 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10609961\/10609862\/10610696.pdf?arnumber=10610696","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T05:21:25Z","timestamp":1723267285000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10610696\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/icra57147.2024.10610696","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]}}}